


'''simple docstring'''


import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor







def      snake_case_  (    SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				return (data["data"], data["target"])







def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Any							= XGBRegressor(verbosity=0				, random_state=42	)
				xgb.fit(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	)
				# Predict target for test data
				_SCREAMING_SNAKE_CASE					:			str							= xgb.predict(SCREAMING_SNAKE_CASE__	)
				_SCREAMING_SNAKE_CASE					:			List[Any]							= predictions.reshape(len(SCREAMING_SNAKE_CASE__	)				, 1	)
				return predictions







def      snake_case_  (    ):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Tuple							= fetch_california_housing()
				_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= data_handling(SCREAMING_SNAKE_CASE__	)
				_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			str							= train_test_split(
				    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, test_size=0.2_5				, random_state=1	)
				_SCREAMING_SNAKE_CASE					:			int							= xgboost(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	)
				# Error printing
				print(f"""Mean Absolute Error : {mean_absolute_error(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	)}"""	)
				print(f"""Mean Square Error  : {mean_squared_error(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	)}"""	)


if __name__ == "__main__":
				import doctest

				doctest.testmod(verbose=True)
				main()








'''simple docstring'''


import os


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
UpperCAmelCase_						:  List[Any]				  =						'.'


if __name__ == "__main__":
				UpperCAmelCase_						:  Any				  =						os.path.join(REPO_PATH, 'utils/documentation_tests.txt')
				UpperCAmelCase_						:  Dict				  =						[]
				UpperCAmelCase_						:  Union[str, Any]				  =						[]
				with open(doctest_file_path) as fp:
								for line in fp:
												UpperCAmelCase_						:  int				  =						line.strip()
												UpperCAmelCase_						:  str				  =						os.path.join(REPO_PATH, line)
												if not (os.path.isfile(path) or os.path.isdir(path)):
																non_existent_paths.append(line)
												all_paths.append(path)
				if len(non_existent_paths) > 0:
								UpperCAmelCase_						:  int				  =						'\n'.join(non_existent_paths)
								raise ValueError(F"`utils/documentation_tests.txt` contains non-existent paths:\n{non_existent_paths}")
				if all_paths != sorted(all_paths):
								raise ValueError('Files in `utils/documentation_tests.txt` are not in alphabetical order.')




